Notes

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The interquartile range of volumetric percentage of the two groups were 1.0-7.2% and 11.4-31.2%, respectively. Baseline volumetric percentage of infection was significantly higher in severe group, and the cut-off value of it was 10.10%.

Volumetric percentage between severe and common patients was significantly different. Because serial CT scans are systemically performed in patients with COVID-19 pneumonia, this quantitative analysis can simultaneously provide valuable information for physicians to evaluate their clinical course and classify common and severe patients accurately.
Volumetric percentage between severe and common patients was significantly different. Because serial CT scans are systemically performed in patients with COVID-19 pneumonia, this quantitative analysis can simultaneously provide valuable information for physicians to evaluate their clinical course and classify common and severe patients accurately.COVENT-Tester (COVID-19 VENTilator Tester) is a low-cost and open source ventilator tester developed to calibrate the output of medical ventilators, including tidal volume, inspiratory pressure, and oxygen concentration. selleck Currently, there are several open-source ventilator testers, however, existing open-source ventilator testers are unable to measure oxygen concentration. Conversely, commercial ventilator testers with the capacity to measure tidal volume, inspiratory pressure, and oxygen concentration, are very costly. The COVENT-Tester was therefore designed to be low-cost, by using Commercial Off-The-Shelf (COTS) components, to assist the open source community for rapidly manufactured pandemic ventilators. In addition, the COVENT-Tester measurement's validation results show the tester has good accuracy.The coronavirus disease 2019 (COVID-19) is an ongoing pandemic caused by an RNA virus termed as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). SARS-CoV-2 possesses an almost 30kbp long genome. The genome contains open-reading frame 1ab (ORF1ab) gene, the largest one of SARS-CoV-2, encoding polyprotein PP1ab and PP1a responsible for viral transcription and replication. Several vaccines have already been approved by the respective authorities over the world to develop herd immunity among the population. In consonance with this effort, RNA interference (RNAi) technology holds the possibility to strengthen the fight against this virus. Here, we have implemented a computational approach to predict potential short interfering RNAs including small interfering RNAs (siRNAs) and microRNAs (miRNAs), which are presumed to be intrinsically active against SARS-CoV-2. In doing so, we have screened miRNA library and siRNA library targeting the ORF1ab gene. We predicted the potential miRNA and siRNA candidate molecules utilizing an array of bioinformatic tools. By extending the analysis, out of 24 potential pre-miRNA hairpins and 131 siRNAs, 12 human miRNA and 10 siRNA molecules were sorted as potential therapeutic agents against SARS-CoV-2 based on their GC content, melting temperature (Tm), heat capacity (Cp), hybridization and minimal free energy (MFE) of hybridization. This computational study is focused on lessening the extensive time and labor needed in conventional trial and error based wet lab methods and it has the potential to act as a decent base for future researchers to develop a successful RNAi therapeutic.The infectious bronchitis virus (IBV) is still one of the major respiratory viral pathogens of chickens. The IBV infection resulted in a wide range of clinical syndromes in the affected chickens, including respiratory, renal, gonads affections as well as generalized infections. Despite the intensive application of various commercial vaccines against the virus, many outbreaks are still reported in chickens worldwide. Several studies reported the circulation of several strains and genotypes of the IBV in eastern Saudi Arabia. The main goal of the current study was to isolate some of the circulating strains of IBV and assess its ability to reproduce the IBV infections in the challenge birds. Another objective was to monitor the immune status of the infected chickens during the course of this study. To achieve these goals, we used some filed IBV isolates retrieved from an outbreak in a broiler chicken farm in eastern Saudi Arabia in 2014. A total of 220-day-old chickens (110 Ross and 110 native Saudi breed chickens), twenty birds per each group, were used in this study. The chickens in some groups received some IBV vaccines on day one of the experiment, and some are boosted on day 19. All birds were challenged on day 28 of the experiment. Our results showed mild IBV signs in the non-vaccinated control group of chickens; however, the vaccinated chickens did not show any signs of IBV infections. Meanwhile, both the vaccinated and the none- vaccinated birds seroconverted to the IBV as shown by the ELISA results. In conclusion, the response of the IBV infected birds is mainly driven by the vaccination plans they received as a prime-boost regime. Further studies are required for a better understanding of the dynamics of IBV infection in native Saudi chickens.Purpose In sequential imaging studies, there exists rich information from past studies that can be used in prior-image-based reconstruction (PIBR) as a form of improved regularization to yield higher-quality images in subsequent studies. PIBR methods, such as reconstruction of difference (RoD), have demonstrated great improvements in the image quality of subsequent anatomy reconstruction even when CT data are acquired at very low-exposure settings. Approach However, to effectively use information from past studies, two major elements are required (1) registration, usually deformable, must be applied between the current and prior scans. Such registration is greatly complicated by potential ambiguity between patient motion and anatomical change-which is often the target of the followup study. (2) One must select regularization parameters for reliable and robust reconstruction of features. Results We address these two major issues and apply a modified RoD framework to the clinical problem of lung nodule surveillance.
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